Principal Software Engineer, Performance Tooling

The Artificial Intelligence (AI) Frameworks team at Microsoft develops AI software that enables running AI models everywhere, from world’s fastest AI supercomputers, to servers, desktops, mobile phones, internet of things (IoT) devices and internet browsers. We collaborate with our hardware teams and partners, both internal and external, and operate at the intersection of AI algorithmic innovation, purpose-built AI hardware, systems, and software. We are a team of highly capable and motivated people that pride themselves on a collaborative and inclusive culture. We own inference performance of OpenAI and other state of the art large language model (LLM) models and work directly with OpenAI on the models hosted on the Azure OpenAI service serving some of the largest workloads on the planet with trillions of inferences per day in major Microsoft products, including Office, Windows, Bing, SQL Server, and Dynamics.  

As a Principal Software Engineer - Performance Tooling on the team, you will set technical direction across organizations, define the architecture and engineering strategy for AI performance validation and optimization, and drive execution across hardware, runtime, compiler, and model-serving partners. You will lead the design of benchmarking and performance tooling systems used to evaluate OpenAI and other frontier LLMs across GPUs and Microsoft hardware, identify systemic bottlenecks, and translate performance insights into production-ready improvements that reduce time-to-deploy, improve hardware efficiency, and directly support Microsoft Azure's capex goals. 

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.  

Define and drive the technical strategy for AI performance tooling and validation across multiple layers of the AI software stack, including programming models, compilers, runtimes, libraries, and model-serving APIs. 

Architect scalable benchmarking and regression-detection systems for OpenAI and other state-of-the-art LLMs across GPUs, Microsoft accelerators, and emerging AI hardware platforms. 

Lead deep performance investigations across model architecture, kernels, runtimes, networking, scheduling, and hardware behavior, and guide teams toward durable optimizations for production-scale training and inference. 

Establish performance quality bars, readiness signals, and operating mechanisms that enable faster model and hardware bring-up while reducing regressions, deployment risk, and total hardware footprint. 

Influence and align senior engineers, researchers, product leaders, and hardware partners across Microsoft and OpenAI to deliver high-impact, production-ready AI performance improvements. 

Mentor and raise the technical bar for engineers across teams by modeling engineering excellence, improving design quality, and creating reusable systems that scale beyond a single project or product line. 

Other Requirements: 

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. This includes passing the Microsoft Cloud background check upon hire/transfer and every two years thereafter.